Towards multiple 3D bone surface identification and reconstruction using few 2D X-ray images for intraoperative applications

This article discusses a possible method to use a small number, e.g. 5, of conventional 2D X-ray images to reconstruct multiple 3D bone surfaces intraoperatively. Each bone’s edge contours in X-ray images are automatically identified. Sparse 3D landmark points of each bone are automatically reconstructed by pairing the 2D X-ray images. The reconstructed landmark point distribution on a surface is approximately optimal covering main characteristics of the surface. A statistical shape model, dense point distribution model (DPDM), is then used to fit the reconstructed optimal landmarks vertices to reconstruct a full surface of each bone separately. The reconstructed surfaces can then be visualised and manipulated by surgeons or used by surgical robotic systems

Recent trends, technical concepts and components of computer-assisted orthopedic surgery systems: A comprehensive review

Computer-assisted orthopedic surgery (CAOS) systems have become one of the most important and challenging types of system in clinical orthopedics, as they enable precise treatment of musculoskeletal diseases, employing modern clinical navigation systems and surgical tools. This paper brings a comprehensive review of recent trends and possibilities of CAOS systems. There are three types of the surgical planning systems, including: systems based on the volumetric images (computer tomography (CT), magnetic resonance imaging (MRI) or ultrasound images), further systems utilize either 2D or 3D fluoroscopic images, and the last one utilizes the kinetic information about the joints and morphological information about the target bones. This complex review is focused on three fundamental aspects of CAOS systems: their essential components, types of CAOS systems, and mechanical tools used in CAOS systems. In this review, we also outline the possibilities for using ultrasound computer-assisted orthopedic surgery (UCAOS) systems as an alternative to conventionally used CAOS systems.Web of Science1923art. no. 519

AN AUTOMATED, DEEP LEARNING APPROACH TO SYSTEMATICALLY & SEQUENTIALLY DERIVE THREE-DIMENSIONAL KNEE KINEMATICS DIRECTLY FROM TWO-DIMENSIONAL FLUOROSCOPIC VIDEO

Total knee arthroplasty (TKA), also known as total knee replacement, is a surgical procedure to replace damaged parts of the knee joint with artificial components. It aims to relieve pain and improve knee function. TKA can improve knee kinematics and reduce pain, but it may also cause altered joint mechanics and complications. Proper patient selection, implant design, and surgical technique are important for successful outcomes. Kinematics analysis plays a vital role in TKA by evaluating knee joint movement and mechanics. It helps assess surgery success, guides implant and technique selection, informs implant design improvements, detects problems early, and improves patient outcomes. However, evaluating the kinematics of patients using conventional approaches presents significant challenges. The reliance on 3D CAD models limits applicability, as not all patients have access to such models. Moreover, the manual and time-consuming nature of the process makes it impractical for timely evaluations. Furthermore, the evaluation is confined to laboratory settings, limiting its feasibility in various locations. This study aims to address these limitations by introducing a new methodology for analyzing in vivo 3D kinematics using an automated deep learning approach. The proposed methodology involves several steps, starting with image segmentation of the femur and tibia using a robust deep learning approach. Subsequently, 3D reconstruction of the implants is performed, followed by automated registration. Finally, efficient knee kinematics modeling is conducted. The final kinematics results showed potential for reducing workload and increasing efficiency. The algorithms demonstrated high speed and accuracy, which could enable real-time TKA kinematics analysis in the operating room or clinical settings. Unlike previous studies that relied on sponsorships and limited patient samples, this algorithm allows the analysis of any patient, anywhere, and at any time, accommodating larger subject populations and complete fluoroscopic sequences. Although further improvements can be made, the study showcases the potential of machine learning to expand access to TKA analysis tools and advance biomedical engineering applications

2D and 3D surface image processing algorithms and their applications

This doctoral dissertation work aims to develop algorithms for 2D image segmentation application of solar filament disappearance detection, 3D mesh simplification, and 3D image warping in pre-surgery simulation. Filament area detection in solar images is an image segmentation problem. A thresholding and region growing combined method is proposed and applied in this application. Based on the filament area detection results, filament disappearances are reported in real time. The solar images in 1999 are processed with this proposed system and three statistical results of filaments are presented. 3D images can be obtained by passive and active range sensing. An image registration process finds the transformation between each pair of range views. To model an object, a common reference frame in which all views can be transformed must be defined. After the registration, the range views should be integrated into a non-redundant model. Optimization is necessary to obtain a complete 3D model. One single surface representation can better fit to the data. It may be further simplified for rendering, storing and transmitting efficiently, or the representation can be converted to some other formats. This work proposes an efficient algorithm for solving the mesh simplification problem, approximating an arbitrary mesh by a simplified mesh. The algorithm uses Root Mean Square distance error metric to decide the facet curvature. Two vertices of one edge and the surrounding vertices decide the average plane. The simplification results are excellent and the computation speed is fast. The algorithm is compared with six other major simplification algorithms. Image morphing is used for all methods that gradually and continuously deform a source image into a target image, while producing the in-between models. Image warping is a continuous deformation of a: graphical object. A morphing process is usually composed of warping and interpolation. This work develops a direct-manipulation-of-free-form-deformation-based method and application for pre-surgical planning. The developed user interface provides a friendly interactive tool in the plastic surgery. Nose augmentation surgery is presented as an example. Displacement vector and lattices resulting in different resolution are used to obtain various deformation results. During the deformation, the volume change of the model is also considered based on a simplified skin-muscle model

Contrast-enhanced microCT evaluation of degeneration following partial and full width injuries to the mouse lumbar intervertebral disc

A targeted injury to the mouse intervertebral disc (IVD) is often used to recapitulate the degenerative cascade of the human pathology. Since injuries can vary in magnitude and localization, it is critical to examine the effects of different injuries on IVD degeneration. We thus evaluated the degenerative progression resulting from either a partial- or full-width injury to the mouse lumbar IVD using contrast-enhanced micro-computed tomography and histological analyses. A lateral-retroperitoneal surgical approach was used to access the lumbar IVD, and the injuries to the IVD were produced by either incising one side of the annulus fibrosus or puncturing both sides of the annulus fibrosus. Female C57BL/6J mice of 3-4 months age were used in this study. They were divided into three groups to undergo partial-width, full-width, or sham injuries. The L5/6 and L6/S1 lumbar IVDs were surgically exposed, and then the L6/S1 IVDs were injured using either a surgical scalpel (partial-width) or a 33G needle (full-width), with the L5/6 serving as an internal control. These animals recovered and then euthanized at either 2-, 4-, or 8-weeks after surgery for evaluation. The IVDs were assessed for degeneration using contrast-enhanced microCT (CEµCT) and histological analysis. The high-resolution 3D CEµCT evaluation of the IVD confirmed that the respective injuries were localized within one side of the annulus fibrosus or spanned the full width of the IVD. The full-width injury caused significant deteriorations in the nucleus pulposus, annulus fibrous and at the interfaces after 2 weeks, which was sustained through the 8 weeks, while the partial width injury caused localized disruptions that remained limited to the annulus fibrosus. The use of CEµCT revealed distinct IVD degeneration profiles resulting from partial- and full-width injuries. The partial width injury may serve as an alternative model for IVD degeneration resulting from localized annulus fibrosus injuries

Computer Aided Tools for the Design and Planning of Personalized Shoulder Arthroplasty

La artroplastia de hombro es el tercer procedimiento de reemplazo articular más común, después de la artroplastia de rodilla y cadera, y actualmentees el de más rápido crecimiento en el campo ortopédico. Las principales opciones quirúrgicas incluyen la artroplastia total de hombro (TSA), en la quese restaura la anatomía articular normal, y, para pacientes con un manguito rotador completamente desgarrado, la artroplastia inversa de hombro (RSA), en la que la bola y la cavidad de la articulación glenohumeral se cambian. A pesar del progreso reciente y los avances en el diseño, las tasas de complicaciones reportadas para RSA son más altas que las de la artroplastia de hombro convencional. Un enfoque específico para el paciente, en el que los médicos adaptan el tratamiento quirúrgico a las características del mismo y al estado preoperatorio, por ejemplo mediante implantes personalizados y planificación previa, puede ayudar a reducir los problemas postoperatorios y mejorar el resultado funcional. El objetivo principal de esta tesis es desarrollar y evaluar métodos novedosos para RSA personalizado, utilizando tecnologías asistidas por ordenador de última generación para estandarizar y automatizar las fases de diseño y planificación.Los implantes personalizados son una solución adecuada para el tratamiento de pacientes con pérdida extensa de hueso glenoideo. Sin embargo, los ingenieros clínicos se enfrentan a muchas variables en el diseño de implantes (número y tipo de tornillos, superficie de contacto, etc.) y una gran variabilidad anatómica y patológica. Actualmente, no existen herramientas objetivas para guiarlos a la hora de elegir el diseño óptimo, es decir, con suficiente estabilidad inicial del implante, lo que hace que el proceso de diseño sea tedioso, lento y dependiente del usuario. En esta tesis, se desarrolló una simulación de Virtual Bench Test (VBT) utilizando un modelo de elementos finitos para evaluar automáticamente la estabilidad inicial de los implantes de hombro personalizados. A través de un experimento de validación, se demostró que los ingenieros clínicos pueden utilizar el resultado de Virtual Bench Test como referencia para respaldar sus decisiones y adaptaciones durante el proceso de diseño del implante.Al diseñar implantes de hombro, el conocimiento de la morfología y la calidad ósea de la escápula en toda la población es fundamental. En particular, se tienen en cuenta las regiones con la mejor reserva ósea (hueso cortical) para definir la posición y orientación de los orificios de los tornillos, mientras se busca una fijación óptima. Como alternativa a las mediciones manuales, cuya generalización está limitada por el análisis de pequeños subconjuntos de pacientes potenciales, Statistical Shape Models (SSMs) se han utilizado comúnmente para describir la variabilidad de la forma dentro de una población. Sin embargo, estos SSMs normalmente no contienen información sobre el grosor cortical.Por lo tanto, se desarrolló una metodología para combinar la forma del hueso escapular y la morfología de la cortical en un SSM. Primero, se presentó y evaluó un método para estimar el espesor cortical, a partir de un análisis de perfil de Hounsfield Unit (HU). Luego, utilizando 32 escápulas sanas segmentadas manualmente, se creó y evaluó un modelo de forma estadística que incluía información de la cortical. La herramienta desarrollada se puede utilizar para implantar virtualmente un nuevo diseño y probar su congruencia dentro de una población virtual generada, reduciendo así el número de iteraciones de diseño y experimentos con cadáveres.Las mediciones del alargamiento de los músculos deltoides y del manguito rotador durante la planificación quirúrgica pueden ayudar a los médicos aseleccionar un diseño y una posición de implante adecuados. Sin embargo, tal evaluación requiere la indicación de puntos anatómicos como referencia para los puntos de unión de los músculos, un proceso que requiere mucho tiempo y depende del usuario, ya que a menudo se realiza manualmente. Además, las imágenes médicas, que se utilizan normalmente para la artroplastia de hombro,contienen en su mayoría solo el húmero proximal, lo que hace imposible indicarlos puntos de unión de los músculos que se encuentran fuera del campo de visión de la exploración. Por lo tanto, se desarrolló y evaluó un método totalmente automatizado, basado en SSM, para medir la elongación del deltoides y del manguito rotador. Su aplicabilidad clínica se demostró mediante la evaluación del rendimiento de la estimación automatizada de la elongación muscular para un conjunto de articulaciones artríticas del hombro utilizadas para la planificación preoperatoria de RSA, lo que confirma que es una herramienta adecuada para los cirujanos a la hora de evaluar y refinar las decisiones clínicas.En esta investigación, se dio un paso importante en la dirección de un enfoque más personalizado de la artroplastia inversa de hombro, en el que el manejo quirúrgico, es decir, el diseño y la posición del implante, se adapta a las características específicas del paciente y al estado preoperatorio. Al aplicar tecnologías asistidas por computadora en la práctica clínica, el proceso de diseño y planificación se puede automatizar y estandarizar, reduciendo así los costos y los plazos de entrega. Además, gracias a los métodos novedosos presentados en esta tesis, esperamos en el futuro una adopción más amplia del enfoque personalizado, con importantes beneficios tanto para los cirujanos como para los pacientes.Shoulder arthroplasty is the third most common joint replacement procedure, after knee and hip arthroplasty, and currently the most rapidly growing one in the orthopaedic field. The main surgical options include total shoulder arthroplasty (TSA), in which the normal joint anatomy is restored, and, for patients with a completely torn rotator cuff, reverse shoulder arthroplasty (RSA), in which the ball and the socket of the glenohumeral joint are switched. Despite the recent progress and advancement in design, the reported rates of complication for RSA are higher than those of conventional shoulder arthroplasty. A patient-specific approach, in which clinicians adapt the surgical management to patient characteristics and preoperative condition, e.g. through custom implants and pre-planning, can help to reduce postoperative problems and improve the functional outcome. The main goal of this thesis is to develop and evaluate novel methods for personalized RSA, using state-of-the-art computer aided technologies to standardize and automate the design and planning phases. Custom implants are a suitable solution when treating patients with extensive glenoid bone loss. However, clinical engineers are confronted with an enormous implant design space (number and type of screws, contact surface, etc.) and large anatomical and pathological variability. Currently, no objective tools exist to guide them when choosing the optimal design, i.e. with sufficient initial implant stability, thus making the design process tedious, time-consuming, and user-dependent. In this thesis, a Virtual Bench Test (VBT) simulation was developed using a finite element model to automatically evaluate the initial stability of custom shoulder implants. Through a validation experiment, it was shown that the virtual test bench output can be used by clinical engineers as a reference to support their decisions and adaptations during the implant design process. When designing shoulder implants, knowledge about bone morphology and bone quality of the scapula throughout a certain population is fundamental. In particular, regions with the best bone stock (cortical bone) are taken into account to define the position and orientation of the screw holes, while aiming for an optimal fixation. As an alternative to manual measurements, whose generalization is limited by the analysis of small sub-sets of the potential patients, Statistical Shape Models (SSMs) have been commonly used to describe shape variability within a population. However, these SSMs typically do not contain information about cortical thickness. Therefore, a methodology to combine scapular bone shape and cortex morphology in an SSM was developed. First, a method to estimate cortical thickness, starting from a profile analysis of Hounsfield Unit (HU), was presented and evaluated. Then, using 32 manually segmented healthy scapulae, a statistical shape model including cortical information was created and assessed. The developed tool can be used to virtually implant a new design and test its congruency inside a generated virtual population, thus reducing the number of design iterations and cadaver labs. Measurements of deltoid and rotator cuff muscle elongation during surgical planning can help clinicians to select a suitable implant design and position. However, such an assessment requires the indication of anatomical landmarks as a reference for the muscle attachment points, a process that is time-consuming and user-dependent, since often performed manually. Additionally, the medical images, which are normally used for shoulder arthroplasty, mostly contain only the proximal humerus, making it impossible to indicate those muscle attachment points which lie outside of the field of view of the scan. Therefore, a fully-automated method, based on SSM, for measuring deltoid and rotator cuff elongation was developed and evaluated. Its clinical applicability was demonstrated by assessing the performance of the automated muscle elongation estimation for a set of arthritic shoulder joints used for preoperative planning of RSA, thus confirming it a suitable tool for surgeons when evaluating and refining clinical decisions. In this research, a major step was taken into the direction of a more personalized approach to Reverse Shoulder Arthroplasty, in which the surgical management, i.e. implant design and position, is adapted to the patient-specific characteristics and preoperative condition. By applying computer aided technologies in the clinical practice, design and planning process can be automated and standardized, thus reducing costs and lead times. Additionally, thanks to the novel methods presented in this thesis, we expect in the future a wider adoption of the personalized approach, with important benefits both for surgeons and patients.<br /

Augmented reality for computer assisted orthopaedic surgery

In recent years, computer-assistance and robotics have established their presence in operating theatres and found success in orthopaedic procedures. Benefits of computer assisted orthopaedic surgery (CAOS) have been thoroughly explored in research, finding improvements in clinical outcomes, through increased control and precision over surgical actions. However, human-computer interaction in CAOS remains an evolving field, through emerging display technologies including augmented reality (AR) – a fused view of the real environment with virtual, computer-generated holograms. Interactions between clinicians and patient-specific data generated during CAOS are limited to basic 2D interactions on touchscreen monitors, potentially creating clutter and cognitive challenges in surgery. Work described in this thesis sought to explore the benefits of AR in CAOS through: an integration between commercially available AR and CAOS systems, creating a novel AR-centric surgical workflow to support various tasks of computer-assisted knee arthroplasty, and three pre–clinical studies exploring the impact of the new AR workflow on both existing and newly proposed quantitative and qualitative performance metrics. Early research focused on cloning the (2D) user-interface of an existing CAOS system onto a virtual AR screen and investigating any resulting impacts on usability and performance. An infrared-based registration system is also presented, describing a protocol for calibrating commercial AR headsets with optical trackers, calculating a spatial transformation between surgical and holographic coordinate frames. The main contribution of this thesis is a novel AR workflow designed to support computer-assisted patellofemoral arthroplasty. The reported workflow provided 3D in-situ holographic guidance for CAOS tasks including patient registration, pre-operative planning, and assisted-cutting. Pre-clinical experimental validation on a commercial system (NAVIO®, Smith & Nephew) for these contributions demonstrates encouraging early-stage results showing successful deployment of AR to CAOS systems, and promising indications that AR can enhance the clinician’s interactions in the future. The thesis concludes with a summary of achievements, corresponding limitations and future research opportunities.Open Acces